Bring your real work in.
Connect PDF, Excel, PPT, Word, images, and internal knowledge — the pipeline starts from the documents and tasks your team already works with.
Baryon AI Work Pipeline measures what AI adoption actually changed — work → execute → output → verify → measure → standardize. One flagship product, already in paid production, compared before and after on the same metrics.
AI adoption is up, but most organizations cannot explain what it changed — account counts do not measure AX. Baryon AI Work Pipeline connects work execution and impact measurement in a single flow, so the work itself becomes the evidence.
Connect PDF, Excel, PPT, Word, images, and internal knowledge — the pipeline starts from the documents and tasks your team already works with.
Research, comparison, analysis, and writing run through chat and parallel subagents — multiple models, one seat, no setup.
Conversations turn into editable PPTX decks and shareable documents — outputs your organization can review, not chat transcripts.
See which internal documents grounded each answer, with citations recorded. What is not in your documents is not presented as evidence.
Model, tokens, cost, latency, and success are recorded per project automatically — usage, quality, and efficiency measured in three layers.
Recurring executions are fixed into organizational work pipelines and policies — compared before and after on the same metrics.
Hanwha Aerospace & Hanwha Systems, Ara, Shinyoung, and Hanjung NCS run their work on it — Ara moved from short onboarding to always-on API-integrated operations. Every execution leaves its record, citation, cost, and output behind, automatically.
Stage 1 · Short onboarding — start measuring in your real work. Per-seat, same-day start, no installation, no server, no setup. Your first execution data lands the day you begin.
Stage 2 · Annual subscription — always-on operations with the AX impact report included: before-and-after comparison on the same metrics, per-project policies and cost caps, and an admin console. Quoted through an adoption consultation.
We analyzed two years of AI adoption activity at Korea's largest listed companies through their public record. The market gap is not AI training — it is the operations layer that measures what happens after execution.
Work redesign was the most active adoption area, yet impact and ROI measurement was the only empty one — across every counting method we applied. Source: Baryon Labs research BL-IA-2026-03.
Hanwha Aerospace, Ara, Yonsei University, ALPACO, LIKELION, and Karrot — training and operations delivered on the same product, with feedback flowing straight back into it.
Baryon Labs operates its own domains with the same agents and measurement stack we sell. The faster we improve it for ourselves, the faster it improves for you — that speed is the moat.
Vibecamp and our recurring online sessions teach AI workflows — then the practice continues on chat.baryon.ai, where every execution becomes measurable AX data. Training → hands-on → measurement, one pipeline.
Baryons are the heavy particles — protons, neutrons — that compose everyday matter. We named the lab after the unsexy thing that everything else depends on. The same way our tools work: the agents you see are built on small, durable primitives that already shipped.
Two stages. Short onboarding: per-seat, same-day start — measure in your real work from day one. Annual subscription: always-on operations with the AX impact report included. Both are quoted by organization size and scope — talk to us. Vibecamp individual courses stay free; enterprise training is subscription-based.
Yes. miri reads any git repository and writes patches as PRs. miridev-cli has JSON-RPC and exec modes meant for CI. baryon-core is MIT-licensed and runtime-agnostic — pair it with your own LLM provider.
Quietly, always. If you've shipped an agent in production and we'd recognize the codebase, send us a link and a sentence. Email's at the bottom.
Korea has world-class engineers and very few peer cohorts for AI-native building. We run vibecamp bilingually because the lessons travel but the network is local.